System and Method For Providing Data Corresponding To Physical Objects

ABSTRACT

There is provided a system and method for providing data describing a physical structure. An exemplary method comprises defining an unstructured grid that corresponds to a three-dimensional physical structure. The unstructured grid comprises data representative of a property of interest. At least one filter object and a selection criterion are defined. A portion of the unstructured grid data that meets the selection criterion relative to the filter object is selected.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional PatentApplication 61,328,052, filed Apr. 26, 2010, entitled SYSTEM AND METHODFOR PROVIDING DATA CORRESPONDING TO PHYSICAL OBJECTS, the entirety ofwhich is incorporated by reference herein.

FIELD

The present techniques relate to providing three-dimensional (3D) dataand/or visualizations of data corresponding to physical objects andanalysis thereof. In particular, an exemplary embodiment of the presenttechniques relates to providing filtered data on a fully unstructuredgrid.

BACKGROUND

This section is intended to introduce various aspects of the art, whichmay be associated with embodiments of the disclosed techniques. Thisdiscussion is believed to assist in providing a framework to facilitatea better understanding of particular aspects of the disclosedtechniques. Accordingly, it should be understood that this section is tobe read in this light, and not necessarily as admissions of prior art.

Three-dimensional (3D) model construction and visualization have beenwidely accepted by numerous disciplines as a mechanism for analyzing,communicating, and comprehending complex 3D datasets. Examples ofstructures that can be subjected to 3D analysis include the earth'ssubsurface, facility designs and the human body, to name just threeexamples.

The ability to easily interrogate and explore 3D models is one aspect of3D visualization. Relevant models may contain both 3D volumetric objectsand co-located 3D polygonal objects. Examples of volumetric objects areseismic volumes, MRI scans, reservoir simulation models, and geologicmodels. Interpreted horizons, faults and well trajectories are examplesof polygonal objects. In some cases, there is a need to view thevolumetric and polygonal objects concurrently to understand theirgeometric and property relations. If every cell of the 3D volumetricobject is rendered fully opaque, other objects in the scene will ofnecessity be occluded, and so it becomes advantageous at times to rendersuch volumetric objects with transparency so that other objects may beseen through them. These 3D model interrogation and exploration tasksare important during exploration, development and production phases inthe oil and gas industry. Similar needs exist in other industries.

3D volumetric objects may be divided into two basic categories:structured grids and unstructured grids. Those of ordinary skill in theart will appreciate that other types of grids may be defined on aspectrum between purely structured grids and purely unstructured grids.Both structured and unstructured grids may be rendered for a user toexplore and understand the associated data. There are large numbers ofknown volume rendering techniques for structured grids. Many such knowntechniques render a full 3D volume with some degree of transparency,which enables the user to see through the volume. However, determiningrelations of 3D object properties is difficult, because it is hard todetermine the exact location of semi-transparent data.

A first known way to view and interrogate a 3D volume is to render across-section through the 3D volume. The surface of the intersectionbetween the cross-section and the 3-D volume may be rendered as apolygon with texture-mapped volume cell properties added thereto. In thecase of a structured grid such as seismic or a medical scan, the usercan create cross-sections along one of the primary directions: XY(inline or axial), XZ (cross-line or coronal) and YZ (time slice orsagital). A traditional cross-section spans the extent of the object. Inthis case other objects such as horizons, wells or the like arepartially or completely occluded and it is difficult to discern 3Drelationships between objects.

This effect is shown in FIG. 1, which is a 3D graph 100 of a subsurfaceregion. The graph 100, which may provide a visualization of 3D data fora structured grid or an unstructured grid, shows a first cross-section102, a second cross-section 104, a third cross-section 106 and a fourthcross-section 108. Each of the four cross-sections shown in FIG. 1 ischosen to allow a user to see data in a physical property model thatcomprises data representative of a property of interest. However, afirst horizon 110 and a second horizon 112, as well as data displayed oncross-sections 102, 104 and 106 which also may be of interest to a user,are mostly obscured or occluded by the visualizations of the fourcross-sections.

A ribbon section, also called an arbitrary vertical cross-section, isone attempt to make traditional cross-sectional visual representationsmore flexible for structured grids. To create a ribbon section, the userdigitizes a polyline on one face of a volume bounding box, probe face,slice, or any arbitrary surface. The polyline is extruded through thevolume creating a curtain or ribbon, and the volumetric data from theintersection of the ribbon with the volume is painted on the curtainsurface.

This concept of arbitrary vertical cross-sections (i.e. ribbon sections)is depicted in

FIG. 2, which is a 3D graph 200 of a subsurface region showing anarbitrary vertical cross-section defined by a polyline having twosegments. The graph 200, which may provide a visualization of 3D datafor a structured grid or a geologic model, shows an arbitrary verticalcross-section defined by a first line segment 202 and a second linesegment 204. Although the arbitrary cross-section shown in FIG. 2 isless intrusive than the cross-sections shown in FIG. 1, portions of afirst horizon 206 and a second horizon 208 are still occluded as long asthe arbitrary cross-section is displayed.

U.S. Pat. Nos. 7,098,908 and 7,248,258 disclose a system and method foranalyzing and imaging 3D structured grids using ribbon sections. In onedisclosed system, a ribbon section is produced which may include aplurality of planes projected from a polyline. The polyline includes oneor more line segments preferably formed within a plane. The projectedplanes intersect the 3D volume data set and the data located at theintersection may be selectively viewed. The polyline may be edited orvaried by editing or varying the control points which define thepolyline. Physical phenomena represented within the three-dimensionalvolume data set may be tracked. A plurality of planes may besuccessively displayed in the three-dimensional volume data set fromwhich points are digitized related to the structure of interest tocreate a spline curve on each plane. The area between the spline curvesis interpolated to produce a surface representative of the structure ofinterest, which may for example be a fault plane described by thethree-dimensional volume data set. This may allow a user to visualizeand interpret the features and physical parameters that are inherent inthe three-dimensional volume data set.

Some 3D visualization techniques are suitable for grid structures thatfall between fully structured grids and fully unstructured grids. Onesuch visualization technique relates to the use of reservoir simulationgrids based on geologic models.

As used herein, the term “geologic model” refers to a model that istopologically structured in I,J,K space but geometrically varied. Ageologic model may be defined in terms of nodes and cells. Geologicmodels can also be defined via pillars (columnar cells or 2.5D grid—i.e.a 3D grid extruded from a 2D grid). A geologic model may be visuallyrendered as a shell (i.e. a volume with data displayed only on outersurfaces).

As noted, a geologic model may be thought of as an intermediate stepbetween completely structured and completely unstructured grids. In itssimplest form, a geologic model may comprise a structured grid withdeformed geometry. In a geologic model, cells may be uniquelyaddressable, but their geometries are not entirely implicit. Because ofdeformation, a cell's corner vertices cannot be calculated from just thegrid origin and unit vectors along with the cell's indices. However,each cell is still a polyhedron with six faces. An index may be used tofind its neighbors. Each cell (except the boundary faces) shares sixfaces with other cells, and shares eight corners with other cells.Neighboring cells sharing a vertex may also be addressed. Those ofordinary skill in the art will appreciate that there may be variationson this basic definition of a geologic model. For example, a geologicmodel may comprise keyed out cells, faults and pinch outs. However, thebasic indices still apply and the majority of cells comprise six-facedpolyhedrons. In addition, reservoir simulation grids that are based ongeologic models may retain (i, j, k) cell indices, while explicitlystoring cell geometries.

U.S. Pat. No. 6,106,561 discloses a reservoir simulation grid that isbased on a geologic model. The grid is produced by a simulation griddingprogram that includes a structured gridder. The structured gridderincludes a structured areal gridder and a block gridder. The structuredareal gridder builds an areal grid on an uppermost horizon of an earthformation by performing the following steps: (1) building a boundaryenclosing one or more fault intersection lines on the horizon, andbuilding a triangulation that absorbs the boundary and the faults; (2)building a vector field on the triangulation; (3) building a web ofcontrol lines and additional lines inside the boundary which have adirection that corresponds to the direction of the vector field on thetriangulation, thereby producing an areal grid; and (4) post-processingthe areal grid so that the control lines and additional lines areequi-spaced or smoothly distributed. The block gridder of the structuredgridder will drop coordinate lines down from the nodes of the areal gridto complete the construction of a three dimensional structured grid. Areservoir simulator will receive the structured grid and generate a setof simulation results which are displayed on a 3D viewer for observationby a workstation operator.

U.S. Pat. No. 6,018,497 describes a system having a single grid made upof a mixture of structured and unstructured elements. Unstructured cellsare used around wells because there is higher resolution data in theseareas. Other areas are represented by regular grid cells. The softwaregenerates (i, j, k) indices for the whole grid, so at the end the gridhas the characteristics of a structured grid and it may be classified asa semi-structured grid. In particular, a method and apparatus generatesgrid cell property information that is adapted for use by a computersimulation apparatus which simulates properties of an earth formationlocated near one or more wellbores. An interpretation workstationincludes at least two software programs stored therein: a first programand a second simulation program which is responsive to output dataproduced from the first program for generating a set of simulationresults. The set of simulation results are displayed on a workstationdisplay monitor of the workstation. The first program will: receive welllog and seismic data which indicates the location of each layer of aformation near a wellbore, and then grid each layer of the formation,the grid being comprised of a plurality of cells. The first program willthen generate more accurate data associated with each cell, such as thetransmissibility of well fluid through each cell. The more accurate datafor each cell originating from the first program will be transmitted tothe second simulation program. The second simulation program willrespond to the more accurate data for each cell of the grid from thefirst program by generating a set of more accurate simulation resultsfor each cell of the grid. The second simulation program will overlaythe more accurate simulation result for each cell onto each of thecorresponding cells of the grid which is being generated and displayedon the workstation display by the first program. As a result, theworkstation will display each layer of the earth formation where eachlayer is gridded with a plurality of cells, and each cell has its ownparticular color which corresponds in numerical value to the particularmore accurate simulation result (e.g., pressure or saturation) thatcorresponds to that cell.

Another known attempt to provide a 3D visualization is for a user torender one or more subsets of 3D structured grid data. This technique iscalled volume probing or volume roaming (SGI OpenGL VolumizerProgrammer's Guide) or alternatively just probing, as discussed in U.S.Pat. Nos. 6,765,570 and 6,912,468. The subsets may be created, resized,shaped, and moved interactively by the user within the whole 3D volumedata set. As a subset changes shape, size, or location in response touser input, the image is re-drawn at a rate so as to be perceived asreal-time by the user. In this manner, the user is allegedly able tovisualize and interpret the features and physical parameters that areinherent in the 3D volume data set.

FIG. 3 is a 3D graph 300 of a subsurface region showing an area ofinterest identified by a 3-D data subset. The graph 300, which mayprovide a visualization of 3D data for a structured grid, shows a 3Ddata subset 302. A first horizon 304 and a second horizon 306 are alsoshown. In the graph 300, the second horizon 306 is partially occluded bythe 3D data subset 302. Because of the manner in which the data subset302 was selected, it cannot easily be moved to reveal the occludedportion of the second horizon 306.

Another approach to rendering 3D object properties is the use ofisosurfaces, which represent data points having the same or similarproperty values. An isosurface is a 3D analog to a contour line on amap, which connects points of the same elevation. Contour lines on a 2Dmap allow an understanding of the location of mountains and valleys,even though the map is flat. Similarly, isosurfaces can help provide anunderstanding of property distribution in a 3D volume. There are numberof ways to create isosurfaces. One such algorithm is known as a marchingcube algorithm. This technique, however, is not widely used to visualizeseismic data, because seismic property values change by a large amountevery time a sedimentary layer is encountered. If isosurfaces arerendered in seismic data, the result would be a visualization resemblinga large number of pancake-like surfaces stacked on top each other.Accordingly, isosurfaces are not commonly used in the oil and gasindustry.

FIG. 4 is an isosurface rendering 400 of an unstructured grid. Theisosurface rendering 400 comprises a first isosurface 402, a secondisosurface 404, and third isosurfaces 406. Each of the first isosurface402, the second isosurface 404, and the third isosurfaces 406 representsurfaces, each of which represents a common parameter value in a 3Dregion.

Another technique for displaying data corresponding to a 3D region isvolume rendering a space with different attributes corresponding todifferent values of a parameter of interest. For example, differentregions of the 3D region may be shaded in different colors based onvariations in a parameter of interest.

FIG. 5 is a volume rendering 500 of an unstructured grid. The volumerendering 500 comprises a first region 502 and a second region 504. Thefirst region 502 and the second region 504 are shaded differently toindicate that the value of a parameter of interest is in a differentrange in the first region 502 relative to the second region 504.

Another known method of producing visualizations of data represented ina structured grid relates to the use of a probe. A user can quicklyexplore a 3D volume by moving the probe. U.S. Pat. No. 6,765,570discloses a system and method for analyzing and imaging 3D volume datasets using a 3D sampling probe. According to a disclosed system, anumber of sampling probes can be created, shaped, and movedinteractively by the user within the whole 3D volume data set. As thesampling probe changes shape, size, or location in response to userinput, the image is re-drawn at a rate so as to be perceived asreal-time by the user. In this manner, the user is allegedly able tovisualize and interpret the features and physical parameters that areinherent in the 3D volume data set.

U.S. Pat. No. 6,912,468 discloses a method and apparatus forcontemporaneous utilization of a higher order probe in pre-stack andpost-stack seismic domains. The disclosed method includes initiating ahigher order probe at a three-dimensional coordinate in a post-stackseismic volume and instantiating a pre-stack seismic data content forthe higher order probe.

A publication by Speray, D. and Kennon, S., entitled “Volume Probe:Interactive Data Exploration on Arbitrary Grids”, Computer Graphics,November, 1990 describes a technique for probing an unstructured gridusing one or three sheets where a sheet is a planar cutting surface thatmay have limited extents. This functionality is very limiting in thatthe planar sheets can not represent real objects and probing with realobjects is a significant advantage to users.

U.S. Patent Application Publication No. 2009/0303233 describes a systemand method for probing geometrically irregular grids. The disclosurespecifically relates to systems and methods for imaging a 3D volume ofgeometrically irregular grid data. Various types of probes and displaysare used to render the geometrically irregular grid data, in real-time,and analyze the geometrically irregular grid data. The grids describedrequire topologically regular I,J,K indexing. This indexing is arequirement for the described probing technique, which significantlylimits the types of data on which the described method can operate.

Another technique for displaying data on structured or unstructuredgrids is filtering. A known method demonstrates filtering based onproperty thresholds where only those elements of the grid that meet thespecified property threshold criteria are selected for visualization.

A publication by Castanie, et al., entitled “3D Display of Propertiesfor Unstructured Grids”, 23rd Gocad Meeting, June, 2003, discusses aco-rendering technique in which one unstructured grid property isrendered on an isosurface created from another property.

SUMMARY

An exemplary embodiment of the present techniques comprises a method forproviding data describing a physical structure. The exemplary methodcomprises defining an unstructured grid that corresponds to athree-dimensional physical structure. The unstructured grid comprisesdata representative of a property of interest. At least one filterobject and a selection criterion are defined. A portion of theunstructured grid data that meets the selection criterion relative tothe filter object is selected.

One exemplary method comprises creating a visualization of the selectedportion of the unstructured grid. Another exemplary method comprisescreating a three-dimensional visualization of the selected portion ofthe unstructured grid.

In an exemplary embodiment of the present techniques, the selectioncriterion comprises an intersection with the filter object. Theselection criteria may comprise containment by the filter object. Theselection criteria may also comprise a distance from the filter object.In addition, the selection criteria may comprise a direction from thefilter object. The selection criterion may comprise filter objectexclusion. The selection criterion may also comprise a combination of anintersection, a containment, a distance, a difference, and/or anexclusion. The selected portion of the unstructured grid may containelements that at least partially meet the selection criteria.

In one exemplary embodiment, the filter object is moved to a newlocation. A portion of the unstructured grid data that meets theselection criterion relative to the new location is selected.

In another exemplary embodiment, the geometry of the filter object ismodified to create a modified filter object geometry definition. Aportion of the unstructured grid data that meets the selection criterionrelative to the modified filter object geometry definition is selected.

In still another exemplary embodiment, the selection criterion ischanged. A portion of the unstructured grid data that meets the newselection criterion relative to the filter object is selected.

One exemplary embodiment according to the present techniques relates toa computer system that is adapted to provide data describing a physicalstructure. The computer system may comprise a processor and a tangible,machine-readable storage medium that stores machine-readableinstructions for execution by the processor. The machine-readableinstructions may comprise code that, when executed by the processor, isadapted to cause the processor to define an unstructured grid thatcorresponds to a three-dimensional physical structure, the unstructuredgrid comprising data representative of a property of interest. Themachine-readable instructions may also comprise code that, when executedby the processor, is adapted to cause the processor to define at leastone filter object and a selection criterion. The machine-readableinstructions may additionally comprise code that, when executed by theprocessor, is adapted to cause the processor to select a portion of theunstructured grid data that meets the selection criterion relative tothe filter object.

In one exemplary computer system, the tangible, machine-readableinstructions comprise code that, when executed by the processor, isadapted to cause the processor to create a visualization of the selectedportion of the unstructured grid. The selection criterion may comprisean intersection with the filter object. The selected portion of theunstructured grid may contain elements that at least partially meet theselection criteria.

In another exemplary computer system, the tangible, machine-readableinstructions comprise code that, when executed by the processor, isadapted to cause the processor to move the filter object to a newlocation. The machine-readable instructions may also comprise code that,when executed by the processor, is adapted to cause the processor toselect a portion of the unstructured grid data that meets the selectioncriterion relative to the new location.

An exemplary embodiment of the present techniques relates to a methodfor producing hydrocarbons from an oil and/or gas field using datadescribing the oil and/or gas field. Such an exemplary method maycomprise defining an unstructured grid that corresponds to athree-dimensional portion of the oil and/or gas field. The unstructuredgrid may comprise data representative of a property of interest in theoil and/or gas field. The exemplary method of producing hydrocarbons mayalso comprise defining at least one filter object and a selectioncriterion. A portion of the unstructured grid data that meets theselection criterion relative to the filter object may be selected.Hydrocarbons may be extracted from the oil and/or gas field based on theselected portion of the unstructured grid.

DESCRIPTION OF THE DRAWINGS

Advantages of the present techniques may become apparent upon reviewingthe following detailed description and the accompanying drawings inwhich:

FIG. 1 is a 3D graph of a subsurface region showing a combination offour cross-sections with two horizons mostly occluded;

FIG. 2 is a 3D graph of a subsurface region showing an arbitraryvertical cross-section with two horizons partially occluded;

FIG. 3 is a 3D graph of a subsurface region showing a region of interestidentified by a sub-volume probe with one horizon partially occluded;

FIG. 4 is an isosurface rendering of an unstructured grid;

FIG. 5 is a volume rendering of an unstructured grid;

FIG. 6 is a 3D graph showing a probe region in an unstructured gridaccording to an exemplary embodiment of the present techniques;

FIG. 7 is a 3D graph showing the use of cross-sections to describe aprobe region in an unstructured grid according to an exemplaryembodiment of the present techniques;

FIG. 8 is a 3D graph showing a filtered visual representation in anunstructured grid according to an exemplary embodiment of the presenttechniques;

FIG. 9 is a process flow diagram showing a method for providing datathat represents a physical object according to exemplary embodiments ofthe present techniques;

FIG. 10 is a process flow diagram showing a method for producinghydrocarbons from a subsurface region such as an oil and/or gas fieldaccording to exemplary embodiments of the present techniques; and

FIG. 11 is a block diagram of a computer network that may be used toperform a method for providing visualizations of data that represents aphysical object according to exemplary embodiments of the presenttechniques.

DETAILED DESCRIPTION

In the following detailed description section, specific embodiments aredescribed in connection with preferred embodiments. However, to theextent that the following description is specific to a particularembodiment or a particular use, this is intended to be for exemplarypurposes only and simply provides a description of the exemplaryembodiments. Accordingly, the present techniques are not limited toembodiments described herein, but rather, it includes all alternatives,modifications, and equivalents falling within the spirit and scope ofthe appended claims.

At the outset, and for ease of reference, certain terms used in thisapplication and their meanings as used in this context are set forth. Tothe extent a term used herein is not defined below, it should be giventhe broadest definition persons in the pertinent art have given thatterm as reflected in at least one printed publication or issued patent.

As used herein, the term “3D seismic data volume” refers to a 3D datavolume of discrete x-y-z or x-y-t data points, where x and y are notnecessarily mutually orthogonal horizontal directions, z is the verticaldirection, and t is two-way vertical seismic signal travel time. Insubsurface models, these discrete data points are often represented by aset of contiguous hexahedrons known as cells or voxels. Each data point,cell, or voxel in a 3D seismic data volume typically has an assignedvalue (“data sample”) of a specific seismic data attribute such asseismic amplitude, acoustic impedance, or any other seismic dataattribute that can be defined on a point-by-point basis.

As used herein, the term “cell” refers to a closed volume formed by acollection of faces, or a collection of nodes that implicitly definefaces.

As used herein, the term “computer component” refers to acomputer-related entity, either hardware, firmware, software, acombination thereof, or software in execution. For example, a computercomponent can be, but is not limited to being, a process running on aprocessor, a processor, an object, an executable, a thread of execution,a program, and/or a computer. One or more computer components can residewithin a process and/or thread of execution and a computer component canbe localized on one computer and/or distributed between two or morecomputers.

As used herein, the terms “computer-readable medium” or “tangiblemachine-readable medium” refer to any tangible storage that participatesin providing instructions to a processor for execution. Such a mediummay take many forms, including but not limited to, non-volatile media,and volatile media. Non-volatile media includes, for example, NVRAM, ormagnetic or optical disks. Volatile media includes dynamic memory, suchas main memory. Computer-readable media may include, for example, afloppy disk, a flexible disk, hard disk, magnetic tape, or any othermagnetic medium, magneto-optical medium, a CD-ROM, any other opticalmedium, a RAM, a PROM, and EPROM, a FLASH-EPROM, a solid state mediumlike a holographic memory, a memory card, or any other memory chip orcartridge, or any other physical medium from which a computer can read.When the computer-readable media is configured as a database, it is tobe understood that the database may be any type of database, such asrelational, hierarchical, object-oriented, and/or the like. Accordingly,exemplary embodiments of the present techniques may be considered toinclude a tangible storage medium or tangible distribution medium andprior art-recognized equivalents and successor media, in which thesoftware implementations embodying the present techniques are stored.

As used herein, the term “cross-section” refers to a plane thatintersects a structured grid or an unstructured grid.

As used herein, the term “face” refers to a collection of vertices.

As used herein, the term “filter” refers to the selection of a subset of3D model topological elements (e.g. nodes, faces, cells) based on someselection criteria. Such criteria may be explicit, such as the selectionof elements in a given list, or may be defined procedurally. Suchprocedural criteria may include, but are not limited to, selection ofelements within some particular range or ranges of property values,within some proximity to features of interest, and/or any combination(intersection, union, difference, etc.) of other filters. Filter resultsare often visualized to provide users a better understanding of theirdata. Additional processing might also occur due to filter results.

As used herein, the term “filter object” refers to a 3D construct havinga geometry not defined by the structured or unstructured grid beingfiltered. For example, a filter object for a 3D model may be defined asa well path, fault, polyline, pointset, closed or open surface, horizonor a separate 3D model.

As used herein, the term “horizon” refers to a geologic boundary in thesubsurface structures that are deemed important by an interpreter.Marking these boundaries is done by interpreters when interpretingseismic volumes by drawing lines on a seismic section. Each linerepresents the presence of an interpreted surface at that location. Aninterpretation project typically generates several dozen and sometimeshundreds of horizons. Horizons may be rendered using different colors sothat they stand out in a 3D visualization of data.

As used herein, the term “I,J,K space” refers to an internal coordinatesystem for a geo-cellular model, having specified integer coordinatesfor (i,j,k) for consecutive cells. By convention, K represents avertical coordinate. I,J,K space may be used as a sample space in whicheach coordinate represents a single sample value without reference to aphysical characteristic.

As used herein, the term “node” refers to a point defining a topologicallocation in I,J,K space. If a split or fault condition is associatedwith the node, that node may have more than one point associatedtherewith.

As used herein, the term “plane” refers to a two-dimensional surface. Aplane may be flat or curved.

As used herein, the term “probe” refers to a 3D object that is used todisplay grid data. Probes may be open or closed surfaces, horizons,faults, 3D models, polylines, wells, point sets, ribbon sections (i.e.traverses, vertical arbitrary cross-sections) or any other 3D construct.A probe visualization algorithm displays grid data on the probe orvolume renders the grid data inside a closed area defined by the probe.

As used herein, the term “structured grid” refers to a matrix of volumedata points known as voxels. Structured grids may be used with seismicdata volumes.

As used herein, the term “seismic data” refers to a multi-dimensionalmatrix or grid containing information about points in the subsurfacestructure of a field, where the information was obtained using seismicmethods. Seismic data typically is represented using a structured grid.Seismic attributes or properties are cell- or voxel-based. Seismic datamay be volume rendered with opacity or texture mapped on a surface.

As used herein, the term “simulation model” refers to a structured gridor an unstructured grid with collections of points, faces and cells.

As used herein, the term “stacking” is a process in which traces (i.e.,seismic data recorded from a single channel of a seismic survey) areadded together from different records to reduce noise and improveoverall data quality. Characteristics of seismic data (e.g., time,frequency, depth) derived from stacked data are referred to as“post-stack” but are referred to as “pre-stack” if derived fromunstacked data. More particularly, the seismic data set is referred tobeing in the pre-stack seismic domain if unstacked and in the post-stackseismic domain if stacked. The seismic data set can exist in bothdomains simultaneously in different copies.

As used herein, the term “topological elements” refers to the buildingblocks of an object. Points, faces, or cells are the most commonexamples.

As used herein, the term “unstructured grid” refers to a collection ofcells with arbitrary geometries. Each cell can have the shape of aprism, hexahedron, or other more complex 3D geometries. When compared tostructured grids, unstructured grids can better represent actual datasince unstructured grids can contain finer (i.e. smaller) cells in onearea with sudden changes in value of a property, and coarser (i.e.larger) cells elsewhere where the value of the property changes moreslowly. Finer cells may also be used in areas having more accuratemeasurements or data certainty (for example, in the vicinity of a well).The flexibility to define cell geometry allows the unstructured grid torepresent physical properties better than structured grids. In addition,unstructured grid cells can also better resemble the actual geometriesof subsurface layers because cell shape is not restricted to a cube andmay be given any orientation. However, all cell geometries need to bestored explicitly, thus an unstructured grid may require a substantialamount of memory. Unstructured grids may be employed in connection withreservoir simulation models. Note that the term unstructured gridrelates to how data is defined and does imply that the data itself hasno structure. For example, one could represent a seismic model as anunstructured grid with explicitly defined nodes and cells. The resultwould necessarily be more memory intensive and inefficient to processand visualize than the corresponding structured definition.

As used herein, the terms “visualization engine” or “VE” refer to acomputer component that is adapted to present a model and/orvisualization of data that represents one or more physical objects.

As used herein, the term “voxel” refers to the smallest data point in a3D volumetric object. Each voxel has unique set of coordinates andcontains one or more data values that represent the properties at thatlocation. Each voxel represents a discrete sampling of a 3D space,similar to the manner in which pixels represent sampling of the 2Dspace. The location of a voxel can be calculated by knowing the gridorigin, unit vectors and the i ,j, k indices of the voxel. As voxels areassumed to have similar geometries (such as cube-shaped), the details ofthe voxel geometries do not need to be stored, thus structured gridsrequire relatively little memory. However, dense sampling may be neededto capture small features, therefore increasing computer memory usagerequirements.

Some portions of the detailed description which follows are presented interms of procedures, steps, logic blocks, processing and other symbolicrepresentations of operations on data bits within a computer memory.These descriptions and representations are the means used by thoseskilled in the data processing arts to most effectively convey thesubstance of their work to others skilled in the art. In the presentapplication, a procedure, step, logic block, process, or the like, isconceived to be a self-consistent sequence of steps or instructionsleading to a desired result. The steps are those requiring physicalmanipulations of physical quantities. Usually, although not necessarily,these quantities take the form of electrical or magnetic signals capableof being stored, transferred, combined, compared, and otherwisemanipulated in a computer system.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise as apparent from the followingdiscussions, it is appreciated that throughout the present application,discussions using the terms such as “defining”, “selecting”,“displaying”, “limiting”, “processing”, “computing”, “obtaining”,“predicting”, “producing”, “providing”, “updating”, “comparing”,“determining”, “adjusting” or the like, refer to the action andprocesses of a computer system, or similar electronic computing device,that transforms data represented as physical (electronic) quantitieswithin the computer system's registers and memories into other datasimilarly represented as physical quantities within the computer systemmemories or registers or other such information storage, transmission ordisplay devices. Example methods may be better appreciated withreference to flow diagrams.

While for purposes of simplicity of explanation, the illustratedmethodologies are shown and described as a series of blocks, it is to beappreciated that the methodologies are not limited by the order of theblocks, as some blocks can occur in different orders and/or concurrentlywith other blocks from that shown and described. Moreover, less than allthe illustrated blocks may be required to implement an examplemethodology. Blocks may be combined or separated into multiplecomponents. Furthermore, additional and/or alternative methodologies canemploy additional, not illustrated blocks. While the figures illustratevarious serially occurring actions, it is to be appreciated that variousactions could occur concurrently, substantially in parallel, and/or atsubstantially different points in time.

As set forth below, exemplary embodiments of the present techniquesrelate to the investigation, interrogation and visualization ofunstructured volumetric objects. More specifically, exemplaryembodiments relate to the provision of visualizations of datarepresented in the form of an unstructured grid using techniques ofprobe selection and filtering.

An exemplary embodiment of the present techniques relates to avisualization engine or VE that supports volume rendered unstructuredgrids. Moreover, a VE according to the present techniques supportscreating an unstructured probe type that allows clients to volume renderinside a probe or to render properties on the probe faces.

A probe object according to the present technique may comprise anotherobject describing a physical structure (e.g. a well, horizon, fault, oreven another 3D model) or may be a non-planar synthetic object createdby a user. Further, probe objects according to the present techniquescan be closed and contain volume and allow for volume rendering insidethis closed volume.

According to an exemplary embodiment of the present techniques, a probeprovides a visualization of a model on the probe geometry. Moreover, thepresent techniques relate to identifying model data with a 3D objectthat is not defined by the geometry of the grid associated with themodel data. Examples of probing according to an exemplary embodiment ofthe present techniques include selecting the unstructured grid data thatis intersected by a well, or contained by a closed surface, or withinsome distance to another object and displaying the data on the probe.This is in contrast to a filter, which delineates a subset of thetopological elements belonging to a model and visualizes the subset.

Exemplary embodiments of the present technique may be combined withother techniques to provide new workflows. For example, a model A may befiltered based on a surface B. The result may be used to probe a modelC.

In addition, an exemplary embodiment of the present technique may beused on a completely unstructured data model and does not require anindex domain. Thus, such an exemplary embodiment may operate in asimilar manner on both geologic and simulation models as well as anunstructured grid.

FIG. 6 is a 3D graph showing a probe region in an unstructured gridaccording to an exemplary embodiment of the present techniques. Thegraph is generally referred to by the reference number 600. A legend 602shows a directional reference for an x-axis, a y-axis and a z-axis.

The graph 600 shows an unstructured grid 604, which may correspond to aportion of a 3D space. The unstructured grid 604 represents a pluralityof cells, each of which embodies data about a property of interest forthe 3D space. Moreover, the cells are defined because they represent aregion of the 3D space having a common value (or range of values) forthe property of interest. The cells of the unstructured grid 604 are,therefore, defined by their data content relative to a property ofinterest (for example, porosity). The cells do not have a uniformgeometry.

According to an exemplary embodiment of the present techniques, novisualization of the property of interest is shown for most of theunstructured grid 604. Moreover, the graph 600 shows a visualization ofa probe region 606. The probe region 606, which may be referred to as avolume of interest herein, is located by a user in a portion of theunstructured grid for which the user wishes to observe the property ofinterest. In the exemplary embodiment shown in FIG. 6, the probe region606 is generally spherical. Those of ordinary skill in the art willappreciate that the shape of the probe region may take the form of awide range of geometries depending on specific applications. Accordingto an exemplary embodiment of the present techniques, a probe is anobject that comprises a set of topological elements, at least one ofwhich does not share a common plane with the other topological elementsthat define the probe. This probe configuration allows a user to obtaindata about a wide range of subsurface features, such as horizons, wellpaths or the like.

As shown in FIG. 6, a VE according to exemplary embodiments of thepresent technique provides a visualization of cell data for cells thatinteract with the probe region 606. Moreover, the visualization of theunstructured grid data is displayed on the geometry defined by theprobe. The visualization may include a representation of datacorresponding to the property of interest. For example, datacorresponding to the cells within the probe region 606 may be shown indifferent colors on the geometry defined by the probe to indicatedifferent values of the property of interest.

To create a visualization by selecting a probe region or volume ofinterest, a three-dimensional structure such as a sphere or a polyhedronis created in such a way that it at least partially intersects anunstructured grid. The three-dimensional structure represents a proberegion. The probe region may be chosen based on any criteria that a usermay wish to employ. In particular, the user may select an area for theprobe region for which a visualization of data corresponding to theproperty of interest is desired.

A property of the unstructured grid may then be rendered on the faces ofthe three-dimensional structure of the probe region. For example, avalue or color corresponding to each cell in the probe region may bedisplayed as a portion of the visualization. Alternatively, anunstructured grid property may be volume rendered on the interior of thethree-dimensional structure of the probe region. As yet anotheralternative, a structured grid may be created within thethree-dimensional volume of interest. A property of the unstructuredgrid may be sampled and used to volume render the structured grid. Afterthe application of any of these alternative techniques, thethree-dimensional volume of interest may be moved and the associatedgrid property re-rendered.

In addition, one or more vertices of the three-dimensional region ofinterest may be moved. The corresponding property may then bere-rendered on the geometry of the probe. In an exemplary embodiment, afilter object may be moved from an initial location to a new location. Aportion of unstructured grid data that meets selection criteria relativeto the new location may be selected.

A portion of a geometric definition of a filter object may be modifiedto create a modified filter object geometry definition. A portion of anunstructured grid data that meets the selection criterion relative tothe modified filter object geometry definition may be selected.

A region within a probe may be volume rendered as a structured grid. Forthe case of structured grid volume rendering, a box probe on anunstructured grid may be volume rendered by replacing a six-sided probewith a structured grid and sampling onto that grid for volume renderingof the probe. The user would be able to tune the granularity of thesampling relative to the interactive requirements to achieve a balancebetween interaction and image quality.

FIG. 7 is a 3D graph showing the use of cross-sections to describe aprobe region in an unstructured grid according to an exemplaryembodiment of the present techniques. The graph is generally referred toby the reference number 700. The graph 700 is useful in explaining thedefinition of a 3D probe region using cross-sections.

The graph 700 comprises an unstructured grid 702. For purposes ofsimplicity, no constituent cells of the unstructured grid 702 are shownin FIG. 7. The unstructured grid 702 is intersected by a firstcross-sectional plane 704 and a second cross-sectional plane 706. As setforth above, the first cross-sectional plane 704 and a secondcross-sectional plane 706 may be chosen by the user based on a widerange of considerations. Moreover, the selection of the probe region andsubsequent definition thereof are performed by a user based on one ormore properties of the 3D space represented by the unstructured gridthat may be of interest to the user. An exemplary embodiment of thepresent techniques employs a probe that comprises an object defined by aset of topological elements, at least one of which does not share acommon plane.

The first cross-sectional plane 704 and the second cross-sectional plane706 define a 3D polyhedronal probe region 708. Exemplary embodiments ofthe present techniques may comprise a VE that is adapted to render avisualization of data corresponding to a property of interest on thesurfaces of the 3D polyhedronal probe region 708. In addition, othertechniques may be employed to provide a useful visualization using the3D polyhedronal probe region 708. For example, the interior of the 3Dpolyhedronal probe region 708 may be represented as a structured grid,which may be volume rendered.

FIG. 8 is a 3D graph showing a filtered visual representation in anunstructured grid according to an exemplary embodiment of the presenttechniques. The graph is generally referred to by the reference number800. A legend 802 shows a directional reference for an x-axis, a y-axisand a z-axis.

The graph 800 shows an unstructured grid 804, which may correspond to aportion of a 3D space. The unstructured grid 804 represents a pluralityof cells, each of which embodies data about a property of interest forthe 3D space. Moreover, the cells are defined because they represent aregion of the 3D space having a common value (or range of values) forthe property of interest. As described herein, a filtering techniqueaccording to the present techniques allows a user to define a filterobject corresponding to an item of interest such as a well path. Thedefinition of the filter object is not based on cells in a gridcorresponding to a physical property model. The filter object providesdata from the grid cells for cells that are intersected by the filterobject.

According to an exemplary embodiment of the present techniques, novisualization of the property of interest is shown for most of theunstructured grid 804. However, a visualization of cell data may beprovided based on one or more filter criterion selected by a user. Byway of example, the graph 800 includes a well path 806, which is anexample of a fixed object in the 3D region. A user may be interested inviewing a visualization of data corresponding to the property ofinterest for cells that meet a specific filter criterion. As shown inFIG. 8, the graph 800 includes a filter region 808, which includes cellsthat are within a specific user-selected filter distance of the wellpath 806.

A visualization of the filter region 808 shows the cell values for theproperty of interest for the cells that meet the filter criterion. Forexample, the cells within the filter region 808 may be represented bycorresponding data values or may be shown in different colors toindicate different values of the property of interest.

In general, a visualization may be created using filtering by selectinga range of a cell geometry or one or more cell property values. Cellsthat meet the filtering criteria are selected. This process may berepeated as desired for any number of filters.

If multiple filters are used, the different filters may be combinedusing Boolean operations such as UNION, SUBTRACT, NEGATE, INTERSECTIONor the like. Cells may then be selected based on the result of thechosen Boolean operation(s). A visualization of the selected cells maythen be created.

Examples of filters that may be created by Boolean operations include,without limitation, property thresholds, distances from other objects,surface or line intersections, i,j,k topological identification, userdefined regions or the like. These filters may operate on a point(vertex) topology, a face topology, and/or a cell topology to filterdown to only the topological elements that meet the criteria. Theresulting subset of the model geometry is then provided for display.

FIG. 9 is a process flow diagram showing a method for providing datathat represents a physical object according to exemplary embodiments ofthe present techniques. The process is generally referred to by thereference number 900. The process 900 may be executed using one or morecomputer components of the type described below with reference to FIG.11. Such computer components may comprise one or more tangible,machine-readable media that stores computer-executable instructions. Theprocess 900 begins at block 902.

At block 904, an unstructured grid that corresponds to athree-dimensional physical structure is defined. The unstructured gridmay comprise data representative of a property of interest. At least onefilter object and selection criterion are defined, as shown at block906. At block 908, a portion of the unstructured grid data that meetsthe selection criterion relative to the filter object is selected. Theprocess ends at block 910.

FIG. 10 is a process flow diagram showing a method for producinghydrocarbons from an oil and/or gas field using data describing aphysical structure according to exemplary embodiments of the presenttechniques. The process is generally referred to by the reference number1000. Those of ordinary skill in the art will appreciate that thepresent techniques may facilitate the production of hydrocarbons byproducing visualizations that allow geologists, engineers and the liketo determine a course of action to take to enhance hydrocarbonproduction from a subsurface region. By way of example, a visualizationproduced according to an exemplary embodiment of the present techniquesmay allow an engineer or geologist to determine a well placement toincrease production of hydrocarbons from a subsurface region. At block1002, the process begins.

At block 1004, an unstructured grid that corresponds to athree-dimensional portion of the oil and/or gas field is defined. Theunstructured grid may comprise data representative of a property ofinterest in the oil and/or gas field. At least one filter object and aselection criterion are defined, as shown at block 1006. At block 1008,a portion of the unstructured grid data that meets the selectioncriterion relative to the filter object is selected.

Hydrocarbons are extracted from the oil and/or gas field based on theselected portion of the unstructured grid, as shown at block 1010. Atblock 1012, the process ends.

FIG. 11 is a block diagram of a computer network that may be used toperform a method for providing visualizations of data that represents aphysical object according to exemplary embodiments of the presenttechniques. A central processing unit (CPU) 1102 is coupled to systembus 1104. The CPU 1102 may be any general-purpose CPU, although othertypes of architectures of CPU 1102 (or other components of exemplarysystem 1100) may be used as long as CPU 1102 (and other components ofsystem 1100) supports the inventive operations as described herein. TheCPU 1102 may execute the various logical instructions according tovarious exemplary embodiments. For example, the CPU 1102 may executemachine-level instructions for performing processing according to theoperational flow described above in conjunction with FIG. 9 or FIG. 10.

The computer system 1100 may also include computer components such as arandom access memory (RAM) 1106, which may be SRAM, DRAM, SDRAM, or thelike. The computer system 1100 may also include read-only memory (ROM)1108, which may be PROM, EPROM, EEPROM, or the like. RAM 1106 and ROM1108 hold user and system data and programs, as is known in the art. Thecomputer system 1100 may also include an input/output (I/O) adapter1110, a communications adapter 1122, a user interface adapter 1116, anda display adapter 1118. The I/O adapter 1110, the user interface adapter1116, and/or communications adapter 1122 may, in certain embodiments,enable a user to interact with computer system 1100 in order to inputinformation.

The I/O adapter 1110 preferably connects a storage device(s) 1112, suchas one or more of hard drive, compact disc (CD) drive, floppy diskdrive, tape drive, etc. to computer system 1100. The storage device(s)may be used when RAM 1106 is insufficient for the memory requirementsassociated with storing data for operations of embodiments of thepresent techniques. The data storage of the computer system 1100 may beused for storing information and/or other data used or generated asdisclosed herein. The communications adapter 1122 may couple thecomputer system 1100 to a network (not shown), which may enableinformation to be input to and/or output from system 1100 via thenetwork (for example, the Internet or other wide-area network, alocal-area network, a public or private switched telephony network, awireless network, any combination of the foregoing). User interfaceadapter 1116 couples user input devices, such as a keyboard 1124, apointing device 1114, and/or output devices, such as a speaker(s) (notshown) of the computer system 1100. The display adapter 1118 is drivenby the CPU 1102 to control the display on a display device 1120 to, forexample, display information or a representation pertaining to a portionof a subsurface region under analysis, such as displaying datadescribing a physical structure, according to certain exemplaryembodiments.

The architecture of system 1100 may be varied as desired. For example,any suitable processor-based device may be used, including withoutlimitation personal computers, laptop computers, computer workstations,and multi-processor servers. Moreover, embodiments may be implemented onapplication specific integrated circuits (ASICs) or very large scaleintegrated (VLSI) circuits. In fact, persons of ordinary skill in theart may use any number of suitable structures capable of executinglogical operations according to exemplary embodiments of the presenttechniques.

The present techniques may be susceptible to various modifications andalternative forms, and the exemplary embodiments discussed above havebeen shown only by way of example. However, the present techniques arenot intended to be limited to the particular embodiments disclosedherein. Indeed, the present techniques include all alternatives,modifications, and equivalents falling within the spirit and scope ofthe appended claims.

1. A method for providing data describing a physical structure, themethod comprising: defining an unstructured grid that corresponds to athree-dimensional physical structure, the unstructured grid comprisingdata representative of a property of interest; defining at least onefilter object and a selection criterion; and selecting a portion of theunstructured grid data that meets the selection criterion relative tothe filter object.
 2. The method recited in claim 1, comprising creatinga visualization of the selected portion of the unstructured grid.
 3. Themethod recited in claim 1, comprising creating a three-dimensionalvisualization of the selected portion of the unstructured grid.
 4. Themethod recited in claim 1, wherein the selection criterion comprises anintersection with the filter object.
 5. The method recited in claim 1,wherein the selection criterion comprises containment by the filterobject.
 6. The method recited in claim 1, wherein the selectioncriterion comprises a distance from the filter object.
 7. The methodrecited in claim 6, wherein the selection criterion comprises adirection from the filter object.
 8. The method recited in claim 1,wherein the selection criterion comprises filter object exclusion. 9.The method recited in claim 1, wherein the selection criterion comprisesa combination of an intersection, a containment, a distance, adifference, and/or an exclusion.
 10. The method recited in claim 1,wherein the selected portion of the unstructured grid contains elementsthat at least partially meet the selection criteria.
 11. The methodrecited in claim 1, comprising: moving the filter object to a newlocation; and selecting a portion of the unstructured grid data thatmeets the selection criterion relative to the new location.
 12. Themethod recited in claim 1, comprising: modifying a portion of thegeometric definition of the filter object to create a modified filterobject geometry definition; and selecting a portion of the unstructuredgrid data that meets the selection criterion relative to the modifiedfilter object geometry definition.
 13. The method recited in claim 1,comprising: changing the selection criterion; and selecting a portion ofthe unstructured grid data that meets the new selection criterionrelative to the filter object.
 14. A computer system that is adapted toprovide data describing a physical structure, the computer systemcomprising: a processor; and a tangible, machine-readable storage mediumthat stores machine-readable instructions for execution by theprocessor, the machine-readable instructions comprising: code that, whenexecuted by the processor, is adapted to cause the processor to definean unstructured grid that corresponds to a three-dimensional physicalstructure, the unstructured grid comprising data representative of aproperty of interest; code that, when executed by the processor, isadapted to cause the processor to define at least one filter object anda selection criterion; and code that, when executed by the processor, isadapted to cause the processor to select a portion of the unstructuredgrid data that meets the selection criterion relative to the filterobject.
 15. The computer system recited in claim 14, wherein thetangible, machine-readable instructions comprise code that, whenexecuted by the processor, is adapted to cause the processor to create avisualization of the selected portion of the unstructured grid.
 16. Thecomputer system recited in claim 14, wherein the selection criterioncomprises an intersection with the filter object.
 17. The computersystem recited in claim 14, wherein the tangible, machine-readableinstructions comprise: code that, when executed by the processor, isadapted to cause the processor to move the filter object to a differentlocation; and code that, when executed by the processor, is adapted tocause the processor to select a portion of the unstructured grid datathat meets the selection criterion relative to the different location.18. The computer system recited in claim 14, wherein the selectedportion of the unstructured grid contains elements that at leastpartially meet the selection criteria.
 19. A method for producinghydrocarbons from an oil and/or gas field using data describing the oiland/or gas field, the method comprising: defining an unstructured gridthat corresponds to a three-dimensional portion of the oil and/or gasfield, the unstructured grid comprising data representative of aproperty of interest in the oil and/or gas field; defining at least onefilter object and a selection criterion; selecting a portion of theunstructured grid data that meets the selection criterion relative tothe filter object; and extracting hydrocarbons from the oil and/or gasfield based on the selected portion of the unstructured grid.